


'''simple docstring'''


import math





class        lowercase__    :





							'''simple docstring'''


							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case    ):
											_SCREAMING_SNAKE_CASE					:			List[Any]							= 0.0
											_SCREAMING_SNAKE_CASE					:			int							= 0.0
											for i in range(len(__snake_case    )    ):
															da += math.pow((sample[i] - weights[0][i])       ,   2    )
															da += math.pow((sample[i] - weights[1][i])       ,   2    )
															return 0 if da > da else 1
											return 0






							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case       ,   __snake_case       ,   __snake_case    ):
											for i in range(len(__snake_case    )    ):
															weights[j][i] += alpha * (sample[i] - weights[j][i])
											return weights







def      snake_case_  (    ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Optional[int]							= [[1, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0], [0, 0, 1, 1]]

				# weight initialization ( n, C )
				_SCREAMING_SNAKE_CASE					:			List[Any]							= [[0.2, 0.6, 0.5, 0.9], [0.8, 0.4, 0.7, 0.3]]

				# training
				_SCREAMING_SNAKE_CASE					:			Dict							= SelfOrganizingMap()
				_SCREAMING_SNAKE_CASE					:			List[Any]							= 3
				_SCREAMING_SNAKE_CASE					:			List[Any]							= 0.5

				for _ in range(SCREAMING_SNAKE_CASE__	):
								for j in range(len(SCREAMING_SNAKE_CASE__	)	):
												# training sample
												_SCREAMING_SNAKE_CASE					:			str							= training_samples[j]

												# Compute the winning vector
												_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= self_organizing_map.get_winner(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)

												# Update the winning vector
												_SCREAMING_SNAKE_CASE					:			Any							= self_organizing_map.update(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)

    # classify test sample
				_SCREAMING_SNAKE_CASE					:			Optional[Any]							= [0, 0, 0, 1]
				_SCREAMING_SNAKE_CASE					:			Optional[Any]							= self_organizing_map.get_winner(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)

				# results
				print(f"""Clusters that the test sample belongs to : {winner}"""	)
				print(f"""Weights that have been trained : {weights}"""	)


# running the main() function
if __name__ == "__main__":
				main()








'''simple docstring'''


import math







def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Tuple							= math.loga(math.sqrt(4 * positive_integer + 1	) / 2 + 1 / 2	)

				return exponent == int(SCREAMING_SNAKE_CASE__	)







def      snake_case_  (    SCREAMING_SNAKE_CASE__ = 1 / 1_2345	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			str							= 0
				_SCREAMING_SNAKE_CASE					:			str							= 0

				_SCREAMING_SNAKE_CASE					:			int							= 3
				while True:
								_SCREAMING_SNAKE_CASE					:			Optional[int]							= (integer**2 - 1) / 4
								# if candidate is an integer, then there is a partition for k
								if partition_candidate == int(SCREAMING_SNAKE_CASE__	):
												_SCREAMING_SNAKE_CASE					:			int							= int(SCREAMING_SNAKE_CASE__	)
												total_partitions += 1
												if check_partition_perfect(SCREAMING_SNAKE_CASE__	):
																perfect_partitions += 1
								if perfect_partitions > 0:
												if perfect_partitions / total_partitions < max_proportion:
																return int(SCREAMING_SNAKE_CASE__	)
								integer += 1


if __name__ == "__main__":
				print(F"{solution() = }")




